Pandas Profiling Report

Dataset statistics

Number of variables	20
Number of observations	13645
Missing cells	3336
Missing cells (%)	1.2%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	10.2 MiB
Average record size in memory	783.3 B

Variable types

Categorical	12
Numeric	8

Warnings

`YearsOfExperince` is highly correlated with `GraduationYear`	High correlation
`GraduationYear` is highly correlated with `YearsOfExperince`	High correlation
`CurrentCTC` is highly correlated with `ExpectedCTC`	High correlation
`ExpectedCTC` is highly correlated with `CurrentCTC`	High correlation
`BiasInfluentialFactor` has 3336 (24.4%) missing values	Missing

Reproduction

Analysis started	2021-06-06 14:38:43.203271
Analysis finished	2021-06-06 14:39:17.485822
Duration	34.28 seconds
Software version	pandas-profiling v2.11.0
Download configuration	config.yaml

LanguageOfCommunication
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	948.8 KiB

English	7510
Hindi	4733
Native	1402

Length

Max length	7
Median length	7
Mean length	6.203517772
Min length	5

Characters and Unicode

Total characters	84647
Distinct characters	14
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	English
2nd row	English
3rd row	English
4th row	English
5th row	English

Value	Count	Frequency (%)
English	7510	55.0%
Hindi	4733	34.7%
Native	1402	10.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
english	7510	55.0%
hindi	4733	34.7%
native	1402	10.3%

Most occurring characters

Value	Count	Frequency (%)
i	18378	21.7%
n	12243	14.5%
E	7510	8.9%
g	7510	8.9%
l	7510	8.9%
s	7510	8.9%
h	7510	8.9%
H	4733	5.6%
d	4733	5.6%
N	1402	1.7%
Other values (4)	5608	6.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	71002	83.9%
Uppercase Letter	13645	16.1%

Most frequent character per category

Value	Count	Frequency (%)
i	18378	25.9%
n	12243	17.2%
g	7510	10.6%
l	7510	10.6%
s	7510	10.6%
h	7510	10.6%
d	4733	6.7%
a	1402	2.0%
t	1402	2.0%
v	1402	2.0%

Value	Count	Frequency (%)
E	7510	55.0%
H	4733	34.7%
N	1402	10.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	84647	100.0%

Most frequent character per script

Value	Count	Frequency (%)
i	18378	21.7%
n	12243	14.5%
E	7510	8.9%
g	7510	8.9%
l	7510	8.9%
s	7510	8.9%
h	7510	8.9%
H	4733	5.6%
d	4733	5.6%
N	1402	1.7%
Other values (4)	5608	6.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	84647	100.0%

Most frequent character per block

Value	Count	Frequency (%)
i	18378	21.7%
n	12243	14.5%
E	7510	8.9%
g	7510	8.9%
l	7510	8.9%
s	7510	8.9%
h	7510	8.9%
H	4733	5.6%
d	4733	5.6%
N	1402	1.7%
Other values (4)	5608	6.6%

Age
Real number (ℝ_≥0)

Distinct	19
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	30.69124221
Minimum	24
Maximum	42
Zeros	0
Zeros (%)	0.0%
Memory size	213.2 KiB

Quantile statistics

Minimum	24
5-th percentile	24
Q1	28
median	31
Q3	34
95-th percentile	37
Maximum	42
Range	18
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	3.881378423
Coefficient of variation (CV)	0.1264653414
Kurtosis	-0.6219239727
Mean	30.69124221
Median Absolute Deviation (MAD)	3
Skewness	0.1622960054
Sum	418782
Variance	15.06509846
Monotocity	Not monotonic

Histogram with fixed size bins (bins=19)

Value	Count	Frequency (%)
32	1207	8.8%
34	1157	8.5%
29	1140	8.4%
33	1140	8.4%
35	1122	8.2%
31	1112	8.1%
28	1105	8.1%
27	1100	8.1%
30	1060	7.8%
26	744	5.5%
Other values (9)	2758	20.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
24	721	5.3%
25	733	5.4%
26	744	5.5%
27	1100	8.1%
28	1105	8.1%
29	1140	8.4%
30	1060	7.8%
31	1112	8.1%
32	1207	8.8%
33	1140	8.4%

Value	Count	Frequency (%)
42	41	0.3%
41	62	0.5%
40	56	0.4%
39	52	0.4%
38	365	2.7%
37	375	2.7%
36	353	2.6%
35	1122	8.2%
34	1157	8.5%
33	1140	8.4%

Gender
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.8 KiB

Male	8376
Female	4326
Other	943

Length

Max length	6
Median length	4
Mean length	4.703187981
Min length	4

Characters and Unicode

Total characters	64175
Distinct characters	10
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Male
2nd row	Male
3rd row	Female
4th row	Female
5th row	Male

Value	Count	Frequency (%)
Male	8376	61.4%
Female	4326	31.7%
Other	943	6.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
male	8376	61.4%
female	4326	31.7%
other	943	6.9%

Most occurring characters

Value	Count	Frequency (%)
e	17971	28.0%
a	12702	19.8%
l	12702	19.8%
M	8376	13.1%
F	4326	6.7%
m	4326	6.7%
O	943	1.5%
t	943	1.5%
h	943	1.5%
r	943	1.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	50530	78.7%
Uppercase Letter	13645	21.3%

Most frequent character per category

Value	Count	Frequency (%)
e	17971	35.6%
a	12702	25.1%
l	12702	25.1%
m	4326	8.6%
t	943	1.9%
h	943	1.9%
r	943	1.9%

Value	Count	Frequency (%)
M	8376	61.4%
F	4326	31.7%
O	943	6.9%

Most occurring scripts

Value	Count	Frequency (%)
Latin	64175	100.0%

Most frequent character per script

Value	Count	Frequency (%)
e	17971	28.0%
a	12702	19.8%
l	12702	19.8%
M	8376	13.1%
F	4326	6.7%
m	4326	6.7%
O	943	1.5%
t	943	1.5%
h	943	1.5%
r	943	1.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	64175	100.0%

Most frequent character per block

Value	Count	Frequency (%)
e	17971	28.0%
a	12702	19.8%
l	12702	19.8%
M	8376	13.1%
F	4326	6.7%
m	4326	6.7%
O	943	1.5%
t	943	1.5%
h	943	1.5%
r	943	1.5%

JobProfileIDApplyingFor
Categorical

Distinct	9
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	959.4 KiB

JR85289	4697
JR87525	3416
JR88879	1231
JR89890	1157
JR88873	1123
Other values (4)	2021

Length

Max length	7
Median length	7
Mean length	7
Min length	7

Characters and Unicode

Total characters	95515
Distinct characters	12
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	JR85289
2nd row	JR87525
3rd row	JR87525
4th row	JR87525
5th row	JR70175

Value	Count	Frequency (%)
JR85289	4697	34.4%
JR87525	3416	25.0%
JR88879	1231	9.0%
JR89890	1157	8.5%
JR88873	1123	8.2%
JR81165	681	5.0%
JR79193	678	5.0%
JR88654	420	3.1%
JR70175	242	1.8%

Histogram of lengths of the category

Value	Count	Frequency (%)
jr85289	4697	34.4%
jr87525	3416	25.0%
jr88879	1231	9.0%
jr89890	1157	8.5%
jr88873	1123	8.2%
jr81165	681	5.0%
jr79193	678	5.0%
jr88654	420	3.1%
jr70175	242	1.8%

Most occurring characters

Value	Count	Frequency (%)
8	23707	24.8%
J	13645	14.3%
R	13645	14.3%
5	12872	13.5%
9	9598	10.0%
2	8113	8.5%
7	6932	7.3%
1	2282	2.4%
3	1801	1.9%
0	1399	1.5%
Other values (2)	1521	1.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	68225	71.4%
Uppercase Letter	27290	28.6%

Most frequent character per category

Value	Count	Frequency (%)
8	23707	34.7%
5	12872	18.9%
9	9598	14.1%
2	8113	11.9%
7	6932	10.2%
1	2282	3.3%
3	1801	2.6%
0	1399	2.1%
6	1101	1.6%
4	420	0.6%

Value	Count	Frequency (%)
J	13645	50.0%
R	13645	50.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	68225	71.4%
Latin	27290	28.6%

Most frequent character per script

Value	Count	Frequency (%)
8	23707	34.7%
5	12872	18.9%
9	9598	14.1%
2	8113	11.9%
7	6932	10.2%
1	2282	3.3%
3	1801	2.6%
0	1399	2.1%
6	1101	1.6%
4	420	0.6%

Value	Count	Frequency (%)
J	13645	50.0%
R	13645	50.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	95515	100.0%

Most frequent character per block

Value	Count	Frequency (%)
8	23707	24.8%
J	13645	14.3%
R	13645	14.3%
5	12872	13.5%
9	9598	10.0%
2	8113	8.5%
7	6932	7.3%
1	2282	2.4%
3	1801	1.9%
0	1399	1.5%
Other values (2)	1521	1.6%

HighestDegree
Categorical

Distinct	8
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	940.8 KiB

B.Tech	5619
M.Tech	2026
BCA	1634
MS	1579
Dual M.Tech	1358
Other values (3)	1429

Length

Max length	11
Median length	6
Mean length	5.60498351
Min length	2

Characters and Unicode

Total characters	76480
Distinct characters	16
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	B.Tech
2nd row	B.Tech
3rd row	PhD
4th row	BCA
5th row	Dual M.Tech

Value	Count	Frequency (%)
B.Tech	5619	41.2%
M.Tech	2026	14.8%
BCA	1634	12.0%
MS	1579	11.6%
Dual M.Tech	1358	10.0%
Dual MBA	665	4.9%
PhD	624	4.6%
MCA	140	1.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
b.tech	5619	35.9%
m.tech	3384	21.6%
dual	2023	12.9%
bca	1634	10.4%
ms	1579	10.1%
mba	665	4.2%
phd	624	4.0%
mca	140	0.9%

Most occurring characters

Value	Count	Frequency (%)
h	9627	12.6%
.	9003	11.8%
T	9003	11.8%
e	9003	11.8%
c	9003	11.8%
B	7918	10.4%
M	5768	7.5%
D	2647	3.5%
A	2439	3.2%
u	2023	2.6%
Other values (6)	10046	13.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	33702	44.1%
Uppercase Letter	31752	41.5%
Other Punctuation	9003	11.8%
Space Separator	2023	2.6%

Most frequent character per category

Value	Count	Frequency (%)
T	9003	28.4%
B	7918	24.9%
M	5768	18.2%
D	2647	8.3%
A	2439	7.7%
C	1774	5.6%
S	1579	5.0%
P	624	2.0%

Value	Count	Frequency (%)
h	9627	28.6%
e	9003	26.7%
c	9003	26.7%
u	2023	6.0%
a	2023	6.0%
l	2023	6.0%

Value	Count	Frequency (%)
.	9003	100.0%

Value	Count	Frequency (%)
	2023	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	65454	85.6%
Common	11026	14.4%

Most frequent character per script

Value	Count	Frequency (%)
h	9627	14.7%
T	9003	13.8%
e	9003	13.8%
c	9003	13.8%
B	7918	12.1%
M	5768	8.8%
D	2647	4.0%
A	2439	3.7%
u	2023	3.1%
a	2023	3.1%
Other values (4)	6000	9.2%

Value	Count	Frequency (%)
.	9003	81.7%
	2023	18.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	76480	100.0%

Most frequent character per block

Value	Count	Frequency (%)
h	9627	12.6%
.	9003	11.8%
T	9003	11.8%
e	9003	11.8%
c	9003	11.8%
B	7918	10.4%
M	5768	7.5%
D	2647	3.5%
A	2439	3.2%
u	2023	2.6%
Other values (6)	10046	13.1%

DegreeBranch
Categorical

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

Computer Science	4749
Information Technology	2993
Artificial Intelligence	2001
Electrical	1803
Electronics	1699

Length

Max length	26
Median length	16
Mean length	17.22037376
Min length	10

Characters and Unicode

Total characters	234972
Distinct characters	25
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Electrical
2nd row	Artificial Intelligence
3rd row	Computer Science
4th row	Information Technology
5th row	Computer Science

Value	Count	Frequency (%)
Computer Science	4749	34.8%
Information Technology	2993	21.9%
Artificial Intelligence	2001	14.7%
Electrical	1803	13.2%
Electronics	1699	12.5%
Electrical and Electronics	400	2.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
science	4749	19.6%
computer	4749	19.6%
technology	2993	12.4%
information	2993	12.4%
electrical	2203	9.1%
electronics	2099	8.7%
artificial	2001	8.3%
intelligence	2001	8.3%
and	400	1.7%

Most occurring characters

Value	Count	Frequency (%)
e	27545	11.7%
c	25097	10.7%
n	20229	8.6%
i	20048	8.5%
o	18820	8.0%
t	16046	6.8%
l	15501	6.6%
r	14045	6.0%
	10543	4.5%
m	7742	3.3%
Other values (15)	59356	25.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	200641	85.4%
Uppercase Letter	23788	10.1%
Space Separator	10543	4.5%

Most frequent character per category

Value	Count	Frequency (%)
e	27545	13.7%
c	25097	12.5%
n	20229	10.1%
i	20048	10.0%
o	18820	9.4%
t	16046	8.0%
l	15501	7.7%
r	14045	7.0%
m	7742	3.9%
a	7597	3.8%
Other values (8)	27971	13.9%

Value	Count	Frequency (%)
I	4994	21.0%
C	4749	20.0%
S	4749	20.0%
E	4302	18.1%
T	2993	12.6%
A	2001	8.4%

Value	Count	Frequency (%)
	10543	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	224429	95.5%
Common	10543	4.5%

Most frequent character per script

Value	Count	Frequency (%)
e	27545	12.3%
c	25097	11.2%
n	20229	9.0%
i	20048	8.9%
o	18820	8.4%
t	16046	7.1%
l	15501	6.9%
r	14045	6.3%
m	7742	3.4%
a	7597	3.4%
Other values (14)	51759	23.1%

Value	Count	Frequency (%)
	10543	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	234972	100.0%

Most frequent character per block

Value	Count	Frequency (%)
e	27545	11.7%
c	25097	10.7%
n	20229	8.6%
i	20048	8.5%
o	18820	8.0%
t	16046	6.8%
l	15501	6.6%
r	14045	6.0%
	10543	4.5%
m	7742	3.3%
Other values (15)	59356	25.3%

GraduatingInstitute
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	946.1 KiB

Tier 2	6092
Tier 1	4793
Tier 3	2760

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	81870
Distinct characters	8
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Tier 1
2nd row	Tier 3
3rd row	Tier 1
4th row	Tier 2
5th row	Tier 3

Value	Count	Frequency (%)
Tier 2	6092	44.6%
Tier 1	4793	35.1%
Tier 3	2760	20.2%

Histogram of lengths of the category

Value	Count	Frequency (%)
tier	13645	50.0%
2	6092	22.3%
1	4793	17.6%
3	2760	10.1%

Most occurring characters

Value	Count	Frequency (%)
T	13645	16.7%
i	13645	16.7%
e	13645	16.7%
r	13645	16.7%
	13645	16.7%
2	6092	7.4%
1	4793	5.9%
3	2760	3.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	40935	50.0%
Uppercase Letter	13645	16.7%
Space Separator	13645	16.7%
Decimal Number	13645	16.7%

Most frequent character per category

Value	Count	Frequency (%)
i	13645	33.3%
e	13645	33.3%
r	13645	33.3%

Value	Count	Frequency (%)
2	6092	44.6%
1	4793	35.1%
3	2760	20.2%

Value	Count	Frequency (%)
T	13645	100.0%

Value	Count	Frequency (%)
	13645	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	54580	66.7%
Common	27290	33.3%

Most frequent character per script

Value	Count	Frequency (%)
T	13645	25.0%
i	13645	25.0%
e	13645	25.0%
r	13645	25.0%

Value	Count	Frequency (%)
	13645	50.0%
2	6092	22.3%
1	4793	17.6%
3	2760	10.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	81870	100.0%

Most frequent character per block

Value	Count	Frequency (%)
T	13645	16.7%
i	13645	16.7%
e	13645	16.7%
r	13645	16.7%
	13645	16.7%
2	6092	7.4%
1	4793	5.9%
3	2760	3.4%

LatestDegreeCGPA
Real number (ℝ_≥0)

Distinct	7
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	7.100256504
Minimum	4
Maximum	10
Zeros	0
Zeros (%)	0.0%
Memory size	213.2 KiB

Quantile statistics

Minimum	4
5-th percentile	4
Q1	6
median	7
Q3	8
95-th percentile	9
Maximum	10
Range	6
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.346538857
Coefficient of variation (CV)	0.1896465087
Kurtosis	-0.0380233269
Mean	7.100256504
Median Absolute Deviation (MAD)	1
Skewness	-0.4023318346
Sum	96883
Variance	1.813166894
Monotocity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
7	4738	34.7%
8	3480	25.5%
6	1779	13.0%
9	1554	11.4%
5	1089	8.0%
4	713	5.2%
10	292	2.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
4	713	5.2%
5	1089	8.0%
6	1779	13.0%
7	4738	34.7%
8	3480	25.5%
9	1554	11.4%
10	292	2.1%

Value	Count	Frequency (%)
10	292	2.1%
9	1554	11.4%
8	3480	25.5%
7	4738	34.7%
6	1779	13.0%
5	1089	8.0%
4	713	5.2%

YearsOfExperince
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	12
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	6.547746427
Minimum	1
Maximum	12
Zeros	0
Zeros (%)	0.0%
Memory size	213.2 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	4
median	7
Q3	9
95-th percentile	12
Maximum	12
Range	11
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.426919995
Coefficient of variation (CV)	0.5233739628
Kurtosis	-1.202600586
Mean	6.547746427
Median Absolute Deviation (MAD)	3
Skewness	-0.0155005509
Sum	89344
Variance	11.74378065
Monotocity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
9	1219	8.9%
6	1196	8.8%
11	1166	8.5%
4	1146	8.4%
5	1142	8.4%
7	1130	8.3%
12	1123	8.2%
10	1116	8.2%
8	1114	8.2%
3	1109	8.1%
Other values (2)	2184	16.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1076	7.9%
2	1108	8.1%
3	1109	8.1%
4	1146	8.4%
5	1142	8.4%
6	1196	8.8%
7	1130	8.3%
8	1114	8.2%
9	1219	8.9%
10	1116	8.2%

Value	Count	Frequency (%)
12	1123	8.2%
11	1166	8.5%
10	1116	8.2%
9	1219	8.9%
8	1114	8.2%
7	1130	8.3%
6	1196	8.8%
5	1142	8.4%
4	1146	8.4%
3	1109	8.1%

GraduationYear
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	12
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	2014.452254
Minimum	2009
Maximum	2020
Zeros	0
Zeros (%)	0.0%
Memory size	213.2 KiB

Quantile statistics

Minimum	2009
5-th percentile	2009
Q1	2012
median	2014
Q3	2017
95-th percentile	2020
Maximum	2020
Range	11
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.426919995
Coefficient of variation (CV)	0.001701167148
Kurtosis	-1.202600586
Mean	2014.452254
Median Absolute Deviation (MAD)	3
Skewness	0.0155005509
Sum	27487201
Variance	11.74378065
Monotocity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
2012	1219	8.9%
2015	1196	8.8%
2010	1166	8.5%
2017	1146	8.4%
2016	1142	8.4%
2014	1130	8.3%
2009	1123	8.2%
2011	1116	8.2%
2013	1114	8.2%
2018	1109	8.1%
Other values (2)	2184	16.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2009	1123	8.2%
2010	1166	8.5%
2011	1116	8.2%
2012	1219	8.9%
2013	1114	8.2%
2014	1130	8.3%
2015	1196	8.8%
2016	1142	8.4%
2017	1146	8.4%
2018	1109	8.1%

Value	Count	Frequency (%)
2020	1076	7.9%
2019	1108	8.1%
2018	1109	8.1%
2017	1146	8.4%
2016	1142	8.4%
2015	1196	8.8%
2014	1130	8.3%
2013	1114	8.2%
2012	1219	8.9%
2011	1116	8.2%

CurrentCTC
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	25
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	18.07695126
Minimum	6
Maximum	30
Zeros	0
Zeros (%)	0.0%
Memory size	213.2 KiB

Quantile statistics

Minimum	6
5-th percentile	7
Q1	12
median	18
Q3	24
95-th percentile	29
Maximum	30
Range	24
Interquartile range (IQR)	12

Descriptive statistics

Standard deviation	7.208130046
Coefficient of variation (CV)	0.3987469978
Kurtosis	-1.201778344
Mean	18.07695126
Median Absolute Deviation (MAD)	6
Skewness	-0.01016598468
Sum	246660
Variance	51.95713875
Monotocity	Not monotonic

Histogram with fixed size bins (bins=25)

Value	Count	Frequency (%)
19	598	4.4%
28	589	4.3%
16	575	4.2%
25	574	4.2%
11	572	4.2%
24	567	4.2%
17	562	4.1%
10	559	4.1%
23	556	4.1%
29	556	4.1%
Other values (15)	7937	58.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
6	541	4.0%
7	537	3.9%
8	511	3.7%
9	526	3.9%
10	559	4.1%
11	572	4.2%
12	543	4.0%
13	530	3.9%
14	518	3.8%
15	532	3.9%

Value	Count	Frequency (%)
30	554	4.1%
29	556	4.1%
28	589	4.3%
27	517	3.8%
26	526	3.9%
25	574	4.2%
24	567	4.2%
23	556	4.1%
22	526	3.9%
21	544	4.0%

ExpectedCTC
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	31
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	25.06148772
Minimum	10
Maximum	40
Zeros	0
Zeros (%)	0.0%
Memory size	213.2 KiB

Quantile statistics

Minimum	10
5-th percentile	13
Q1	19
median	25
Q3	31
95-th percentile	37
Maximum	40
Range	30
Interquartile range (IQR)	12

Descriptive statistics

Standard deviation	7.47811922
Coefficient of variation (CV)	0.2983908738
Kurtosis	-1.029886953
Mean	25.06148772
Median Absolute Deviation (MAD)	6
Skewness	0.0004423838647
Sum	341964
Variance	55.92226706
Monotocity	Not monotonic

Histogram with fixed size bins (bins=31)

Value	Count	Frequency (%)
31	600	4.4%
27	598	4.4%
21	584	4.3%
25	569	4.2%
20	559	4.1%
16	555	4.1%
33	551	4.0%
28	544	4.0%
23	544	4.0%
29	538	3.9%
Other values (21)	8003	58.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
10	83	0.6%
11	142	1.0%
12	231	1.7%
13	283	2.1%
14	418	3.1%
15	454	3.3%
16	555	4.1%
17	515	3.8%
18	530	3.9%
19	537	3.9%

Value	Count	Frequency (%)
40	81	0.6%
39	171	1.3%
38	264	1.9%
37	317	2.3%
36	366	2.7%
35	463	3.4%
34	531	3.9%
33	551	4.0%
32	501	3.7%
31	600	4.4%

MartialStatus
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	955.7 KiB

Married	9810
Single	3835

Length

Max length	7
Median length	7
Mean length	6.718944668
Min length	6

Characters and Unicode

Total characters	91680
Distinct characters	10
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Married
2nd row	Married
3rd row	Single
4th row	Married
5th row	Married

Value	Count	Frequency (%)
Married	9810	71.9%
Single	3835	28.1%

Histogram of lengths of the category

Value	Count	Frequency (%)
married	9810	71.9%
single	3835	28.1%

Most occurring characters

Value	Count	Frequency (%)
r	19620	21.4%
i	13645	14.9%
e	13645	14.9%
M	9810	10.7%
a	9810	10.7%
d	9810	10.7%
S	3835	4.2%
n	3835	4.2%
g	3835	4.2%
l	3835	4.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	78035	85.1%
Uppercase Letter	13645	14.9%

Most frequent character per category

Value	Count	Frequency (%)
r	19620	25.1%
i	13645	17.5%
e	13645	17.5%
a	9810	12.6%
d	9810	12.6%
n	3835	4.9%
g	3835	4.9%
l	3835	4.9%

Value	Count	Frequency (%)
M	9810	71.9%
S	3835	28.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	91680	100.0%

Most frequent character per script

Value	Count	Frequency (%)
r	19620	21.4%
i	13645	14.9%
e	13645	14.9%
M	9810	10.7%
a	9810	10.7%
d	9810	10.7%
S	3835	4.2%
n	3835	4.2%
g	3835	4.2%
l	3835	4.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	91680	100.0%

Most frequent character per block

Value	Count	Frequency (%)
r	19620	21.4%
i	13645	14.9%
e	13645	14.9%
M	9810	10.7%
a	9810	10.7%
d	9810	10.7%
S	3835	4.2%
n	3835	4.2%
g	3835	4.2%
l	3835	4.2%

EmpScore
Categorical

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	879.5 KiB

3	5462
4	4184
5	2025
2	1064
1	910

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	13645
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	5
2nd row	5
3rd row	5
4th row	5
5th row	5

Value	Count	Frequency (%)
3	5462	40.0%
4	4184	30.7%
5	2025	14.8%
2	1064	7.8%
1	910	6.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
3	5462	40.0%
4	4184	30.7%
5	2025	14.8%
2	1064	7.8%
1	910	6.7%

Most occurring characters

Value	Count	Frequency (%)
3	5462	40.0%
4	4184	30.7%
5	2025	14.8%
2	1064	7.8%
1	910	6.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	13645	100.0%

Most frequent character per category

Value	Count	Frequency (%)
3	5462	40.0%
4	4184	30.7%
5	2025	14.8%
2	1064	7.8%
1	910	6.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	13645	100.0%

Most frequent character per script

Value	Count	Frequency (%)
3	5462	40.0%
4	4184	30.7%
5	2025	14.8%
2	1064	7.8%
1	910	6.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	13645	100.0%

Most frequent character per block

Value	Count	Frequency (%)
3	5462	40.0%
4	4184	30.7%
5	2025	14.8%
2	1064	7.8%
1	910	6.7%

CurrentDesignation
Categorical

Distinct	8
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	901.0 KiB

SDE	5423
SSE	2745
DS	1716
BA	1710
EM	1342
Other values (3)	709

Length

Max length	3
Median length	3
Mean length	2.619640894
Min length	2

Characters and Unicode

Total characters	35745
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	SSE
2nd row	BA
3rd row	SDE
4th row	SDE
5th row	SDE

Value	Count	Frequency (%)
SDE	5423	39.7%
SSE	2745	20.1%
DS	1716	12.6%
BA	1710	12.5%
EM	1342	9.8%
DA	287	2.1%
SEM	287	2.1%
DE	135	1.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
sde	5423	39.7%
sse	2745	20.1%
ds	1716	12.6%
ba	1710	12.5%
em	1342	9.8%
sem	287	2.1%
da	287	2.1%
de	135	1.0%

Most occurring characters

Value	Count	Frequency (%)
S	12916	36.1%
E	9932	27.8%
D	7561	21.2%
A	1997	5.6%
B	1710	4.8%
M	1629	4.6%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	35745	100.0%

Most frequent character per category

Value	Count	Frequency (%)
S	12916	36.1%
E	9932	27.8%
D	7561	21.2%
A	1997	5.6%
B	1710	4.8%
M	1629	4.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	35745	100.0%

Most frequent character per script

Value	Count	Frequency (%)
S	12916	36.1%
E	9932	27.8%
D	7561	21.2%
A	1997	5.6%
B	1710	4.8%
M	1629	4.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	35745	100.0%

Most frequent character per block

Value	Count	Frequency (%)
S	12916	36.1%
E	9932	27.8%
D	7561	21.2%
A	1997	5.6%
B	1710	4.8%
M	1629	4.6%

CurrentCompanyType
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	975.1 KiB

Startup	6373
Enterprise	4395
MidSized	2877

Length

Max length	10
Median length	8
Mean length	8.177134481
Min length	7

Characters and Unicode

Total characters	111577
Distinct characters	14
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Enterprise
2nd row	MidSized
3rd row	MidSized
4th row	Startup
5th row	Enterprise

Value	Count	Frequency (%)
Startup	6373	46.7%
Enterprise	4395	32.2%
MidSized	2877	21.1%

Histogram of lengths of the category

Value	Count	Frequency (%)
startup	6373	46.7%
enterprise	4395	32.2%
midsized	2877	21.1%

Most occurring characters

Value	Count	Frequency (%)
t	17141	15.4%
r	15163	13.6%
e	11667	10.5%
p	10768	9.7%
i	10149	9.1%
S	9250	8.3%
a	6373	5.7%
u	6373	5.7%
d	5754	5.2%
E	4395	3.9%
Other values (4)	14544	13.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	95055	85.2%
Uppercase Letter	16522	14.8%

Most frequent character per category

Value	Count	Frequency (%)
t	17141	18.0%
r	15163	16.0%
e	11667	12.3%
p	10768	11.3%
i	10149	10.7%
a	6373	6.7%
u	6373	6.7%
d	5754	6.1%
n	4395	4.6%
s	4395	4.6%

Value	Count	Frequency (%)
S	9250	56.0%
E	4395	26.6%
M	2877	17.4%

Most occurring scripts

Value	Count	Frequency (%)
Latin	111577	100.0%

Most frequent character per script

Value	Count	Frequency (%)
t	17141	15.4%
r	15163	13.6%
e	11667	10.5%
p	10768	9.7%
i	10149	9.1%
S	9250	8.3%
a	6373	5.7%
u	6373	5.7%
d	5754	5.2%
E	4395	3.9%
Other values (4)	14544	13.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	111577	100.0%

Most frequent character per block

Value	Count	Frequency (%)
t	17141	15.4%
r	15163	13.6%
e	11667	10.5%
p	10768	9.7%
i	10149	9.1%
S	9250	8.3%
a	6373	5.7%
u	6373	5.7%
d	5754	5.2%
E	4395	3.9%
Other values (4)	14544	13.0%

DepartmentInCompany
Categorical

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	991.4 KiB

Engineering	5749
Design	4393
Customer Success	1570
Product	1232
Finance	701

Length

Max length	16
Median length	11
Mean length	9.398900696
Min length	6

Characters and Unicode

Total characters	128248
Distinct characters	20
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Design
2nd row	Engineering
3rd row	Engineering
4th row	Product
5th row	Engineering

Value	Count	Frequency (%)
Engineering	5749	42.1%
Design	4393	32.2%
Customer Success	1570	11.5%
Product	1232	9.0%
Finance	701	5.1%

Histogram of lengths of the category

Value	Count	Frequency (%)
engineering	5749	37.8%
design	4393	28.9%
customer	1570	10.3%
success	1570	10.3%
product	1232	8.1%
finance	701	4.6%

Most occurring characters

Value	Count	Frequency (%)
n	23042	18.0%
e	19732	15.4%
i	16592	12.9%
g	15891	12.4%
s	9103	7.1%
r	8551	6.7%
E	5749	4.5%
c	5073	4.0%
D	4393	3.4%
u	4372	3.4%
Other values (10)	15750	12.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	111463	86.9%
Uppercase Letter	15215	11.9%
Space Separator	1570	1.2%

Most frequent character per category

Value	Count	Frequency (%)
n	23042	20.7%
e	19732	17.7%
i	16592	14.9%
g	15891	14.3%
s	9103	8.2%
r	8551	7.7%
c	5073	4.6%
u	4372	3.9%
o	2802	2.5%
t	2802	2.5%
Other values (3)	3503	3.1%

Value	Count	Frequency (%)
E	5749	37.8%
D	4393	28.9%
C	1570	10.3%
S	1570	10.3%
P	1232	8.1%
F	701	4.6%

Value	Count	Frequency (%)
	1570	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	126678	98.8%
Common	1570	1.2%

Most frequent character per script

Value	Count	Frequency (%)
n	23042	18.2%
e	19732	15.6%
i	16592	13.1%
g	15891	12.5%
s	9103	7.2%
r	8551	6.8%
E	5749	4.5%
c	5073	4.0%
D	4393	3.5%
u	4372	3.5%
Other values (9)	14180	11.2%

Value	Count	Frequency (%)
	1570	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	128248	100.0%

Most frequent character per block

Value	Count	Frequency (%)
n	23042	18.0%
e	19732	15.4%
i	16592	12.9%
g	15891	12.4%
s	9103	7.1%
r	8551	6.7%
E	5749	4.5%
c	5073	4.0%
D	4393	3.4%
u	4372	3.4%
Other values (10)	15750	12.3%

TotalLeavesTaken
Real number (ℝ_≥0)

Distinct	17
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	11.96702089
Minimum	4
Maximum	20
Zeros	0
Zeros (%)	0.0%
Memory size	213.2 KiB

Quantile statistics

Minimum	4
5-th percentile	4
Q1	8
median	12
Q3	16
95-th percentile	20
Maximum	20
Range	16
Interquartile range (IQR)	8

Descriptive statistics

Standard deviation	4.897836049
Coefficient of variation (CV)	0.4092778057
Kurtosis	-1.195142977
Mean	11.96702089
Median Absolute Deviation (MAD)	4
Skewness	0.01027985964
Sum	163290
Variance	23.98879796
Monotocity	Not monotonic

Histogram with fixed size bins (bins=17)

Value	Count	Frequency (%)
11	861	6.3%
6	856	6.3%
13	842	6.2%
4	827	6.1%
12	818	6.0%
20	812	6.0%
14	802	5.9%
19	802	5.9%
10	794	5.8%
18	792	5.8%
Other values (7)	5439	39.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
4	827	6.1%
5	787	5.8%
6	856	6.3%
7	752	5.5%
8	792	5.8%
9	792	5.8%
10	794	5.8%
11	861	6.3%
12	818	6.0%
13	842	6.2%

Value	Count	Frequency (%)
20	812	6.0%
19	802	5.9%
18	792	5.8%
17	773	5.7%
16	762	5.6%
15	781	5.7%
14	802	5.9%
13	842	6.2%
12	818	6.0%
11	861	6.3%

BiasInfluentialFactor
Categorical

MISSING

Distinct	9
Distinct (%)	0.1%
Missing	3336
Missing (%)	24.4%
Memory size	901.9 KiB

DegreeBranch	2858
Gender	2605
YearsOfExperince	1561
CurrentCompanyType	1174
EmpScore	659
Other values (4)	1452

Length

Max length	18
Median length	12
Mean length	11.63876225
Min length	6

Characters and Unicode

Total characters	119984
Distinct characters	33
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	YearsOfExperince
2nd row	Gender
3rd row	Gender
4th row	DegreeBranch
5th row	YearsOfExperince

Value	Count	Frequency (%)
DegreeBranch	2858	20.9%
Gender	2605	19.1%
YearsOfExperince	1561	11.4%
CurrentCompanyType	1174	8.6%
EmpScore	659	4.8%
HighestDegree	582	4.3%
Ethinicity	328	2.4%
MartialStatus	280	2.1%
LatestDegreeCGPA	262	1.9%
(Missing)	3336	24.4%

Histogram of lengths of the category

Value	Count	Frequency (%)
degreebranch	2858	27.7%
gender	2605	25.3%
yearsofexperince	1561	15.1%
currentcompanytype	1174	11.4%
empscore	659	6.4%
highestdegree	582	5.6%
ethinicity	328	3.2%
martialstatus	280	2.7%
latestdegreecgpa	262	2.5%

Most occurring characters

Value	Count	Frequency (%)
e	24850	20.7%
r	15574	13.0%
n	9700	8.1%
a	6695	5.6%
c	5406	4.5%
p	4568	3.8%
g	4284	3.6%
t	3776	3.1%
h	3768	3.1%
D	3702	3.1%
Other values (23)	37661	31.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	98516	82.1%
Uppercase Letter	21468	17.9%

Most frequent character per category

Value	Count	Frequency (%)
e	24850	25.2%
r	15574	15.8%
n	9700	9.8%
a	6695	6.8%
c	5406	5.5%
p	4568	4.6%
g	4284	4.3%
t	3776	3.8%
h	3768	3.8%
i	3407	3.5%
Other values (9)	16488	16.7%

Value	Count	Frequency (%)
D	3702	17.2%
G	2867	13.4%
B	2858	13.3%
C	2610	12.2%
E	2548	11.9%
Y	1561	7.3%
O	1561	7.3%
T	1174	5.5%
S	939	4.4%
H	582	2.7%
Other values (4)	1066	5.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	119984	100.0%

Most frequent character per script

Value	Count	Frequency (%)
e	24850	20.7%
r	15574	13.0%
n	9700	8.1%
a	6695	5.6%
c	5406	4.5%
p	4568	3.8%
g	4284	3.6%
t	3776	3.1%
h	3768	3.1%
D	3702	3.1%
Other values (23)	37661	31.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	119984	100.0%

Most frequent character per block

Value	Count	Frequency (%)
e	24850	20.7%
r	15574	13.0%
n	9700	8.1%
a	6695	5.6%
c	5406	4.5%
p	4568	3.8%
g	4284	3.6%
t	3776	3.1%
h	3768	3.1%
D	3702	3.1%
Other values (23)	37661	31.4%

FitmentPercent
Real number (ℝ_≥0)

Distinct	4578
Distinct (%)	33.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	75.88009307
Minimum	33.53
Maximum	95.5
Zeros	0
Zeros (%)	0.0%
Memory size	213.2 KiB

Quantile statistics

Minimum	33.53
5-th percentile	42.764
Q1	68.72
median	78.11
Q3	87.99
95-th percentile	93.69
Maximum	95.5
Range	61.97
Interquartile range (IQR)	19.27

Descriptive statistics

Standard deviation	14.89420711
Coefficient of variation (CV)	0.1962860944
Kurtosis	0.3609468789
Mean	75.88009307
Median Absolute Deviation (MAD)	9.64
Skewness	-0.9661750482
Sum	1035383.87
Variance	221.8374055
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
91.2	13	0.1%
91.59	13	0.1%
91.04	12	0.1%
71.8	12	0.1%
85.75	12	0.1%
89.22	11	0.1%
86.74	11	0.1%
89.18	11	0.1%
74.34	11	0.1%
88.85	11	0.1%
Other values (4568)	13528	99.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
33.53	2	< 0.1%
33.58	2	< 0.1%
33.6	1	< 0.1%
33.62	2	< 0.1%
33.65	1	< 0.1%
33.66	1	< 0.1%
33.67	1	< 0.1%
33.71	1	< 0.1%
33.75	3	< 0.1%
33.76	1	< 0.1%

Value	Count	Frequency (%)
95.5	4	< 0.1%
95.49	7	0.1%
95.48	2	< 0.1%
95.47	2	< 0.1%
95.46	2	< 0.1%
95.45	5	< 0.1%
95.44	3	< 0.1%
95.43	1	< 0.1%
95.42	3	< 0.1%
95.41	1	< 0.1%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	LanguageOfCommunication	Age	Gender	JobProfileIDApplyingFor	HighestDegree	DegreeBranch	GraduatingInstitute	LatestDegreeCGPA	YearsOfExperince	GraduationYear	CurrentCTC	ExpectedCTC	MartialStatus	EmpScore	CurrentDesignation	CurrentCompanyType	DepartmentInCompany	TotalLeavesTaken	BiasInfluentialFactor	FitmentPercent
0	English	35	Male	JR85289	B.Tech	Electrical	Tier 1	7	12	2009	21	26	Married	5	SSE	Enterprise	Design	20	YearsOfExperince	95.40
1	English	26	Male	JR87525	B.Tech	Artificial Intelligence	Tier 3	7	3	2018	15	19	Married	5	BA	MidSized	Engineering	6	NaN	67.09
2	English	36	Female	JR87525	PhD	Computer Science	Tier 1	6	6	2015	15	24	Single	5	SDE	MidSized	Engineering	19	Gender	91.26
3	English	29	Female	JR87525	BCA	Information Technology	Tier 2	5	6	2015	16	24	Married	5	SDE	Startup	Product	16	Gender	72.29
4	English	25	Male	JR70175	Dual M.Tech	Computer Science	Tier 3	8	2	2019	24	32	Married	5	SDE	Enterprise	Engineering	10	DegreeBranch	86.34
5	Native	35	Male	JR88879	BCA	Computer Science	Tier 2	9	12	2009	25	29	Married	4	DS	MidSized	Engineering	10	YearsOfExperince	93.23
6	Hindi	31	Male	JR85289	PhD	Computer Science	Tier 1	7	1	2020	12	21	Single	3	SDE	Enterprise	Customer Success	8	CurrentCompanyType	62.29
7	English	32	Male	JR85289	B.Tech	Information Technology	Tier 2	8	9	2012	7	17	Married	3	SSE	MidSized	Engineering	18	DegreeBranch	93.71
8	English	28	Female	JR87525	M.Tech	Electrical	Tier 1	6	2	2019	21	28	Married	4	SDE	Startup	Engineering	7	Gender	91.66
9	Native	31	Female	JR88873	B.Tech	Artificial Intelligence	Tier 2	8	8	2013	21	31	Married	3	SDE	Startup	Customer Success	10	Gender	73.31

Last rows

	LanguageOfCommunication	Age	Gender	JobProfileIDApplyingFor	HighestDegree	DegreeBranch	GraduatingInstitute	LatestDegreeCGPA	YearsOfExperince	GraduationYear	CurrentCTC	ExpectedCTC	MartialStatus	EmpScore	CurrentDesignation	CurrentCompanyType	DepartmentInCompany	TotalLeavesTaken	BiasInfluentialFactor	FitmentPercent
13635	English	35	Male	JR85289	PhD	Artificial Intelligence	Tier 2	5	5	2016	11	19	Married	5	SDE	MidSized	Product	10	NaN	69.49
13636	English	29	Male	JR85289	MCA	Artificial Intelligence	Tier 2	10	3	2018	27	37	Married	3	SEM	Enterprise	Engineering	9	LatestDegreeCGPA	57.14
13637	Hindi	29	Male	JR85289	BCA	Electronics	Tier 1	6	6	2015	9	19	Married	3	SDE	Startup	Product	18	MartialStatus	82.27
13638	English	37	Male	JR87525	M.Tech	Information Technology	Tier 2	8	11	2010	8	18	Single	3	SSE	MidSized	Design	11	DegreeBranch	88.15
13639	Hindi	31	Female	JR88873	BCA	Computer Science	Tier 1	4	8	2013	6	16	Married	3	EM	Startup	Engineering	14	Gender	91.19
13640	English	25	Female	JR87525	Dual MBA	Electrical	Tier 2	7	2	2019	30	34	Married	3	SDE	Startup	Engineering	5	Gender	93.65
13641	Native	29	Other	JR87525	Dual M.Tech	Computer Science	Tier 1	7	6	2015	22	28	Married	4	SSE	Startup	Customer Success	14	NaN	52.90
13642	Hindi	37	Male	JR88873	M.Tech	Artificial Intelligence	Tier 1	8	11	2010	8	16	Single	4	SDE	Enterprise	Design	20	CurrentCompanyType	61.46
13643	Hindi	24	Male	JR87525	B.Tech	Electrical	Tier 2	4	1	2020	27	36	Single	4	SDE	MidSized	Engineering	7	EmpScore	93.64
13644	English	35	Male	JR87525	B.Tech	Electrical	Tier 2	7	12	2009	17	24	Single	3	SSE	Startup	Engineering	16	YearsOfExperince	93.52

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters